In the journey toward optimal spectrum usage, techniques and concepts such as Cognitive
Radio and Dynamic Spectrum Access have enjoyed increasing attention in many
research projects. Dynamic Spectrum Access introduces the need for real-time RF spectrum
information in the form of Radio Environment Maps. This need motivates an investigation
into a hybrid approach of sample measurements and spatial interpolation
as opposed to using conventional propagation models.
Conventional propagation models, both path-general and path-specific, require information
of transmitters within the area of interest. Irregular Terrain Models such as the
Longley-Rice model, further require topographic information in order to consider the
effects of obstacles.
The proposed spatial interpolation technique, kriging, requires no information regarding
transmitters. Furthermore, Ordinary Kriging requires nothing other than measured
samples whereas other kriging variants such as Universal Kriging and Regression
Kriging can use additional information such as topographic data to aid in prediction
accuracy.
This dissertation investigates the performance of the three aforementioned kriging
variants in producing Radio Environment Maps of received power. For practical and
financial reasons, the received power measurement samples are generated using the
Longley-Rice Irregular Terrain Model and are, therefore, simulated measurements.
The experimental results indicate that kriging shows great promise as a tool to generate
Radio Environment Maps. It is found that Ordinary Kriging produces the most
accurate predictions of the three kriging methods and that prediction errors of less than
10 dB can be achieved even when using very low sampling densities. / MSc (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2015
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:nwu/oai:dspace.nwu.ac.za:10394/14462 |
| Date | January 2015 |
| Creators | Boshoff, Willem Hendrik |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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